Heretofore, data compression methods have been designed to compress the bit rate of signals transmitted from a single source. This includes such methods as employed in adaptive delta modulation for voice compression, Joint Photographic Experts Group (JPEG) compression for still images, Motion Picture Expert Group (MPEG) compression for real-time video, and entropy coding for data files. These compression methods are known as source coding in communication or information theory, and they are most effective in situations where there is a single-point to single-point transmission over a physical link, such as a telephone line. These compression methods reduce the amount of information that needs to be transmitted from a source, and they often provide large communication bandwidth reductions in single-point to single-point transmissions.
When, however, a multitude of information sources are transmitted over a single shared physical link as a multitude of data streams, such present day source coding methods alone do not provide the largest possible bandwidth reduction. In such multi-source to multi-source (hereinafter "multi-stream") communications, the signal from each data source is separately compressed using a particular source coding method optimized for that source. The compressed signals are then summed or multiplexed onto a single physical link to be transmitted over a network. In the most popular network known as synchronous time multiplexed ("STM" hereafter) network, each data stream is assigned a certain time slot in a data frame that is predefined by the network. As a result, in an STM network having a plurality of sources communicating over a single physical link, the multiple data streams do not overlap in time, and there is no interaction among the data streams as they are transmitted over the physical link.
The disadvantage of present day STM multistream communications over a single link, however, is that when the different data streams are partially correlated (i.e. when some sources store the same data bit at the same time), redundant data is carried on the communication link. As a result, when the sources are at least partially correlated, present day system can waste a significant amount of transmission bandwidth by communicating redundant data over the link at the same time.
Some present day communication networks reduce the transmission bandwidth of multistream communications over a single physical link by combining the multiple streams into an aggregate signal. Such systems are designed with the assumption that the data streams carried on the communication link are statistically independent of one another. As a result, when the data streams are combined into an aggregate signal transmitted over the single communication link, the bit rate of the aggregate signal is often less than the sum of the individual data stream bit rates. This is known as statistical multiplexing gain (SMG). Typically, SMG is obtained by transmitting information of a momentarily ON source (i.e. a source transmitting during that moment) during the time slot of a momentarily OFF source (a source not transmitting during that moment).
In a present day network designed to take advantage of SMG, such as an asynchronous transfer mode (ATM) network, data buffers are designed as shared buffers with a certain SMG expected. When, however, the data streams are partially correlated (i.e. the sources exhibit similar ON/OFF behavior), the buffers may not have the capacity to handle all the information from the multiple sources. As a result, the buffer overflow forces the network to discard information, thus substantially reducing the network's ability to realize any SMG. Consequently, for ATM networks providing multisource, partially correlated transmission over a single link, there are additional bandwidth problems associated with buffer overflow.